Pronunciation Assessment

Automatic pronunciation assessment (APA) aims to objectively evaluate the pronunciation of non-native speakers, providing valuable feedback for language learning. Current research heavily utilizes deep learning models, particularly transformer-based architectures and large language models, often incorporating multi-task learning to assess multiple aspects of pronunciation (accuracy, fluency, prosody) at various granularities (phoneme, word, sentence). These advancements leverage acoustic features, phone embeddings, and even self-supervised learning to improve accuracy and address challenges like data imbalance and misalignment issues. The resulting improvements in APA systems have significant implications for computer-assisted language learning and speech rehabilitation, offering personalized and efficient feedback mechanisms.